Predicting daily streamflow using rainfall forecasts, a simple loss module and unit hydrographs: two Brazilian catchments

Abstract

The performance of a simple, spatially-lumped, rainfallestreamflow model is compared with that of a more complex, spatially-distributedmodel. In terms of two model-fit statistics it is shown that for two catchments in Brazil (about 30,000 km2and 34,000 km2) with different flowregimes, the simpler catchment models, which are unit hydrograph-based and require only rainfall, streamflow and air temperature data for cal-ibration, perform about as well as more complex catchment models that require additional information from satellite images and digitized mapsof elevation, land-use and soils. Simple catchment models are applied in forecasting mode, using daily rainfall forecasts from a regional weatherforecasting model. The value of the rainfall forecasts, relative to the case where rainfall is known, is assessed for both catchments. The results arediscussed in the context of on-going work to compare different modelling approaches for many other Brazilian catchments, and to apply im-proved forecasting algorithms based on the simple modelling approach to the same, and other, catchments